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1.
INTRODUCTIONInexcavation ,normalanalysisisnotgoodenoughtomeetengineeringneedsduetotheun certaintyofforcesappliedonbracestructures,soilcharacteristics,andsoilmodelused .Toguaranteethattheconstructionprocesscanbesmoothlyperformed ,measurementsinsituareusua…  相似文献   

2.
1 Introduction Direct methanol fuel cell ( DMFC) is desirable toserve as the power systemfor portable devices such ascellular phones , portable computers ,etc. due to thetheoretically high energy density and the liquid fuelused that can be stored and tran…  相似文献   

3.
This study employs the random finite element method (RFEM) to analyze the wall deflection caused by excavation. The RFEM combined random fields of material properties with the FEM through the Monte Carlo simulation. A well-documented excavation case history is employed to evaluate the influence of uncertainty of analysis parameters. This study shows that RFEM can provide reasonable estimations of the exceedance probability of wall deflection caused by excavation, and has the potential to be a useful tool to account for the uncertainties of material and model parameters in the numerical analysis.  相似文献   

4.
仿生模式识别神经网络(BPRNN)同传统BP、RBF神经网络相比具有更好的模式识别能力;训练样本库变更后网络的重新训练时间更小,但该网络构造过程中样本覆盖几何体参数的选择对网络识别率和复杂度有很大影响.本文通过引入蚁群算法来构造并优化网络参数,实验证明该算法法能较好的平衡网络性能和复杂度.  相似文献   

5.
1.IntroductionConsideradelayedneural-networkmodeldescribedbythefollowingfunctionaldifferentialequations.()()()()()()11,nniiiijjjijjjijjtautwgutvgutImt===-++-+邋&1,2,,.in=K(1a)or()()()()()()ttttt=-++-+uAuWGuVGuI&,(1b)where()()()()T12,,,ntututut=轾臌uListhestatevectoroftheneuralnetwork;()12diag,,,naaa=AKisadiagonalmatrixwithpositiveentries,i.e.,0ia>;()ijnnw=Wand()ijnnv=Varetheconnectionweightmatrixanddelayedconnectionweightmatrix,re-spectively;()()()()()()()()T1122,,,nntgutgutgut轾=臌GuKde…  相似文献   

6.
采用误差反传前向人工神经网络模型研究了18种磺酰脲类化合物的结构与除草活性之间的关系.以18种磺酰脲类化合物的量子化学参数作为输入,除草活性作为输出,构建网络模型,取得了较好的预测结果.网络的自相容能力和交叉检验结果良好.该方法还可作为QSAR研究及对有机化合物其他性质进行预测的一种有效手段.  相似文献   

7.
Numerical Analysis of Quality Inspection of Anchorage System   总被引:4,自引:0,他引:4  
Sonoprobe method has been applied in non-destructive inspection of anchorage project.The fundament is that dynamic transient excitation causes the elastic vibration of an anchor bar,and flaws can be estimated or deduced by determining transient response of the anchor bar.FEA numeric solution of hyperbolic equation indicates that deductions must comply with acoustic parameters such as velocity of sound,vibration range,wave shape etc when inspecting interior flaws in the grout of an anchor bar,Based on wavelet packet analysis,the energy eigenvector is a flaw vector,which could be regarded as the basis in the nondestructive inspection of anchors,As a non-linear dynamical system,artifical neural networks dealing with quality insection of gray system have been proved efficient.  相似文献   

8.
李芬 《湘南学院学报》2011,32(5):16-18,72
基于Lyapunov方法和不等式分析技巧,讨论了一类时延细胞神经网络(DCNN)全局渐近稳定性问题,给出了一个新的充分判据,该判据可用于设计出全局稳定的神经网络.  相似文献   

9.
利用同胚映射理论、向量Lyapunov函数思想、M矩阵理论和不等式技术,研究了具有变时滞的细胞神经网络模型的全局指数稳定性,给出了判定平衡点的存在唯一性以及全局指数稳定性的一个判据,并且估计了收敛速度指标.相比一些最近的文献,本文没有采用传统的Lyapunov泛函方法,并且也不需要输出函数在实数集上满足Lipschitz条件,这样就放宽了对网络的要求,使得获得的结果有更广的应用范围.最后的数值例子表明提供的判据不仅保守性小,而且计算简单.  相似文献   

10.
采用主成分分析方法, 就粘性土多指标反映其性质的规律进行了研究. 研究表明, 采用液性指数作为单一指标的传统粘性土物理状态划分方法, 在反映亚粘土和亚砂土性质时不尽合理. 而采用液性指数IL结合孔隙比e反映粉质粘土的特性更加合理. 同样,孔隙比e比液性指数IL能更好地描述亚粘土的天然特性. 采用人工神经网络结合主成分分析, 得出应用孔隙比e和液性指数IL两个指标来预测桩侧摩阻力更为精确. 同时发现在一定临界影响深度范围内(20~30 m), 桩侧摩阻力随深度的增加而增加, 且粘性土的稠度愈硬, 临界深度愈浅.  相似文献   

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